The best way to measure a household’s resilience? Ask those who live there
(posted by The Guardian)
The concept of “resilience” is taking development and humanitarian sectors by storm. Huge amounts of finance are being channelled into “resilience-building” activities, aimed at supporting people and communities to deal more effectively with climate extremes, financial shocks and the many other risks that thr
eaten lives and livelihoods.
Given the pressure on NGOs, governments and donors to demonstrate value for money and support the right people and activities, the race is on to find the best ways of measuring resilience.
Normally, the first step in designing a method for resilience measurement is to consult a group of experts, who consider the assets and capacities that make a household robust. They typically come up with a number of indicators, which can consist of anything from household income and child nutrition to social networks and access to financial capital. Each indicator and characteristic is then mashed together and weighted, often resulting in a single overall score.
While useful, these approaches make a critical assumption: that experts are best placed to evaluate someone else’s resilience. In a new paper for the Overseas Development Institute, we challenge that assumption and propose an alternative approach that has been largely overlooked, but may help to address many of the challenges associated with traditional ways of measuring resilience.
The approach is called subjective resilience, and it starts from the premise that most people have a good understanding of the factors that contribute to their own ability to cope with and adapt to emergencies.
People are asked to consider the factors contributing to their livelihoods and judge how resilient they consider their household to be to given threats. They are also asked to suggest ways to enhance their resilience.
To test the approach, a consortium of international NGOs and research organisations under the Global Resilience Partnership teamed up with Twaweza, an east African movement working to give citizens more power, to speak to 1,300 households across Tanzania, asking people to evaluate their ability to cope with and adapt to the risk of future flooding.
The method used to collect data was also quite unique. Face-to-face interviews were done with people in households from the shores of the Indian Ocean to the Serengeti. Each person was then given a mobile phone and a solar charger, and every few months a call centre rang the same people to ask a series of questions. The answers were then analysed to give accurate and nationally representative information and the whole process was cheaper and easier than traditional surveys.
Given that surveys relating to subjective resilience tend to be shorter than objective ways of measuring resilience (which can often be more than 100 questions long), the approach lends itself to data collection of all kinds across Africa.
Initial results suggest that many of the factors that experts associate with a person’s resilience may not be as important as they had assumed. Factors such as level of education, livelihood, or age have some effect on people’s perceived resilience, but relationships are not as strong as one might traditionally expect. Other factors, like gender, have no apparent impact on evaluations of household resilience, even among female-headed households (typically considered to be one of the most vulnerable groups). Unsurprisingly, the strongest predictor of resilience is wealth and level of income.
While the research is in its early stages, and more work needs to be done to test and develop subjective methods, what we have seen so far raises questions as to whether the indicators we equate with resilience are the right ones.
Above all, subjective assessmenthas the potential to radically change the way that we track resilience and hold governments and civil society to account.
It allows for a bottom-up way of judging the effectiveness of resilience-building initiatives based on the perspectives of the people that matter most: those who are vulnerable and receiving support. One interesting finding from the Tanzania survey was that those who received early warning information about floods rated themselves as far more resilient than those who hadn’t. This suggests that the considerable efforts to support dissemination of weather forecasts and alerts in east Africa may be paying off.
This approach could be used to assess the effectiveness of investments and projects from the perspective of the people benefiting from them. If we listen to their collective voices, we might be better able to hold NGOs, businesses and governments to account.
The same tools could also be applied to evaluate national or international resilience-building initiatives: a difficult feat so far. If international commitments, such as the sustainable development goals, are taken seriously and policies implemented to achieve them, then it is only reasonable to expect a marked difference in how resilient local people perceive themselves to be.
It is clear that subjective assessments are not without weaknesses. People aren’t always aware of all the factors that make them resilient, and some may choose to answer questions inaccurately in order to gain from the outcome of the survey, particularly if there is an assumption that the survey is linked to NGO or government assistance. However, many of the biases can be accounted for by thorough research design and by providing clear information on how the data will be used. Confidence can be taken from the success of similar approaches in other fields, such as subjective wellbeing.
Ultimately, collecting information on subjective resilience isn’t meant to replace traditional measurement entirely. Rather, bottom-up subjective methods should be used alongside objective methods, helping to capture the components of resilience that are difficult to observe and allow people’s perspectives to be heard.
If we can get the measurement process right, this will be an important step forward in gaining a more holistic understanding of what it takes for a household to be resilient to the many risks and threats it faces.
Can new technologies help track resilience?
(posted by Thompson Reuters)
Climate extremes are in the headlines yet again. From the devastation of typhoon Mangkhut in Southeast Asia to Greek wildfires earlier in the year, timely reminders of the importance of resilience-building can be seen everywhere.
It’s therefore reassuring to see resilience quickly climbing to the top of the global development agenda. A $100 million investment by the Global Resilience Partnership and the British government’s £140 million commitment under the Building Resilience and Adaptation to Climate Extremes (BRACED) programme are just two examples of development funders scrambling to launch well-resourced initiatives.
Yet with new-found fame comes new challenges. In particular, how should resilience be tracked and measured?
For a start, no one can agree on a definition for resilience. More importantly, no single recipe exists for supporting the resilience of people and communities across the globe. Factors that help elderly individuals cope with the UK’s ongoing heatwave won’t necessarily be the same as those that support Indian slum-dwellers to deal with recent monsoon flooding.
To make matters harder, collecting information on resilience is costly and time-consuming. With limited resources dedicated to evaluation, most of our current understanding of resilience comes from one-off snap-shots: surveys taken at a single point in time.
These challenges are forcing evaluators to turn to new and unconventional ways of tracking resilience on the ground.
One example is Flowminder, an institute that uses Big Data to map how people respond to disasters. As Cyclone Mahesen came barrelling through Bangladesh in 2013, researchers were able to use anonymised phone records to track people’s movements after the disaster. This allowed unprecedented insights into how long it took people to recover and how people reacted to early warning messages.
Tech-enabled innovations like this are just the tip of the iceberg. A new report by the Overseas Development Institute (ODI) looks at another effort to use mobile phones to gather information on the ground – except instead of tracking people’s movements, researchers use the phones to remotely collect survey data, feeding it back in near-real time.
The team handed out phones and solar chargers to 1,200 individuals in eastern Myanmar. They then set up a small call centre run by a team in nearby Yangon, allowing individuals to be remotely contacted and surveyed every month. After extensive monsoon flooding hit the region in 2016, researchers were able to collect information on how people were coping with the floods up to 12 months later – something that would be far too costly to do using traditional household surveys.
Findings from the mobile phone survey, run by the BRACED progamme, are shedding new light on how we understand resilience.
For one, resilience has long been thought of as largely constant. The Myanmar research turns this perspective on its head, revealing resilience to be a process constantly in flux. Using the mobile phones to track levels of resilience over time shows that it fluctuates significantly after a disaster. In the case of villages surveyed, levels plunged up to six months after the floods, before rebounding rapidly and plateauing up to ten months later.
Using this kind of information to calculate the length of recovery is unprecedented and can arm development actors with valuable information in improving the effectiveness of their activities on the ground.
The surveys also show how flooding wreaks havoc not only for those directly in harm’s way, but all households in the nearby vicinity – even those that self-report as unaffected. Development actors should pay close attention: limiting resilience-building interventions to those physically affected by climate hazards may put those living around them at considerable risk.
Innovations are showcasing the power of technology in unlocking resilience. Not only do mobile surveys like those applied in Myanmar offer unparalleled opportunities to collect survey information at a fraction of the cost of normal face-to-face surveys, they also allow for data to be collected remotely when people are on the move. This is especially useful in post-disaster environments where people are often forced to relocate at short notice, or where it may be unsafe for survey teams to gain access.
While tech-enabled solutions are not a miracle cure, they offer clear opportunities in addressing some of the challenges of traditional measurement approaches. Indeed, as the UN’s secretary general, Antonio Guterres, proudly announces that resilience will be one of the central tenets of his upcoming Climate Summit in 2019, we still don’t know whether billions of pounds worth of resilience funding are having real impact.
Promoting innovation and new ideas in tracking resilience may mean that answering this question is no longer a guessing game.
Sub-Saharan African countries are failing to plan for climate change
Communities around the world are feeling the impacts of climate change already, but many of the most severe effects will be felt in the decades to come, particularly from mid-century onwards. Nowhere is this more apparent than in sub-Saharan Africa which will be one of the hardest hit regions of the world.
Right now, African countries are busy investing in infrastructure and development to help support current economic growth. Many of these long-lived investments – such as ports, large dams, and social infrastructure, such as hospitals and schools – will most likely last well beyond 2050. But by then, Africa’s climate may look quite different to what it does today. Factoring climate change into long-term investments and planning decisions is essential for supporting climate-resilient development – but it’s not happening.
New research, coordinated by the Overseas Development Institute (ODI) and Climate and Development Knowledge Network (CDKN), shows that governments and businesses across sub-Saharan Africa are failing to consider long-term climate information in their investments and planning decisions. This includes studies from Zambia, Malawi, Rwanda, Ghana and Mozambique. The worst case scenario is that poor use of climate information could lock societies into patterns that make them highly vulnerable to droughts, floods, high temperatures or sea-level rise in the future.
Why do decision-makers have this blind spot? First and most importantly, other challenges such as eradicating poverty and promoting access to primary and secondary education are extremely pressing, forcing decision-makers to think and act in short time frames.
Secondly, long-term climate information is often ill-suited to informing local economic, social and environmental contexts in sub-Saharan Africa.
Knowing what the average temperature in 2050 will be for rural Nakuru County, Kenya, is of little practical use. What decision makers really want to know is how higher temperatures are likely to influence water resource availability or crop yields: outcomes that affect local people most. But what decision makers ask for is not often technically possible as there is a lack of information that combines knowledge of future climate with other disciplines such as hydrology or ecology.
There is also a communication mismatch between the producers and users of climate information. The information delivered to decision-makers is often overly technical and easy to misinterpret. Likewise, decision-makers’ needs are rarely fed back to climate scientists.
So what should be done to address this?
Perhaps the most obvious starting point is enhancing the quality and quantity of African climate observation networks and scientific capacity in sub-Saharan Africa. Not only will this help to establish information about past and current climates, it will also help to ‘ground-truth’ climate science by generating local knowledge, perspectives and expertise. Also, these people will be able to act as intermediaries among scientists, policy-makers and practitioners and help with presenting climate information in a format that decision-makers can act upon.
Spending time and resources to understand the local political context, and engaging with local partners, can also help funders and knowledge brokers to communicate climate information more effectively. Above all, funding for climate-related programmes in sub-Saharan Africa needs to shift away from short funding cycles, rigid structures and targets, and donor-driven agendas, and move towards longer-term partnerships between international and national partners.
Importantly, climate information has to be taken up by the people and policies that matter most. Adaptation to climate change still falls under the mandate of ministries such as environment or natural resource management, which are relatively weak in governments. It is only when influential ministries, such as those responsible for economic growth and development, have the incentive and responsibility to act on climate-related issues that effective action occurs.
Importantly, climate information has to be taken up by the people and policies that matter most. Adaptation to climate change still falls under the mandate of ministries such as environment or natural resource management, which are relatively weak in governments. It is only when influential ministries, such as those responsible for economic growth and development, have the incentive and responsibility to act on climate-related issues that effective action occurs.
A large part of this is engaging with high-level ‘champions’ to drive the climate agenda forward. These champions are often vital in gaining legitimacy for climate change discussions and overcoming political obstacles to the use of climate information. In Rwanda, president Paul Kagame’s strong backing for national action on climate change, alongside involvement from relevant ministries, led to climate change being at the heart of the country’s development planning processes.
Lastly, the research raises a number of ethical challenges. Is it justifiable to push for a long-term development agenda in places where addressing current concerns, such as meeting basic economic needs and promoting the wellbeing and development of local communities, is a higher priority? Should we be pushing a long-term agenda where there is little immediate appetite or demand? Sadly, few donors, development agencies or governments are willing to address these questions.
A failure to promote honest and transparent communication of climate information can therefore only result in a further push-back from local decision makers, continuing to put vital infrastructure and long-term development in Sub-Saharan Africa at risk of future climate change.
How can we measure resilience? Mobile phones – and the right questions – can help
People and communities around the world are struggling to deal with the impacts of climate extremes and disasters. At the same time, international finance for supporting people’s resilience to shocks and stresses is limited.
That means understanding how to effectively build resilience is crucial – but to do that we first need to be able to track and measure resilience – something that is often fiendishly difficult.
For example, we might consider a resilient household to be one that can take precautions after receiving early warning of an imminent flood; bounce back quickly from a recent drought; or adapt to increasingly frequent heatwaves. But deciding what factors contribute and are most important to a household’s resilience is a matter fierce debate. Dozens (if not hundreds) of different resilience frameworks exist, each with a unique mix of indicators and ideas.
To make matters worse, collecting information on resilience is hard work. Face-to-face household surveys are expensive, time consuming to run and can take months to set up. This is where the Building Resilience and Adaptation to Climate Extremes and Disasters (BRACED)’s Rapid Response Research (RRR) is making a difference.
RRR is a survey effort that collects information on resilience and post-disaster recovery, currently focusing on the east of Myanmar (in the township of Hpa-An). The initiative is trying two new methods that have the potential to drastically change the way that we collect resilience information.
The first is the use of mobile phones to gather information from households affected by disasters.
With a rise in mobile phone usage across the developing world, contacting people and collecting data has never been quicker, cheaper or more secure. As part of the RRR effort, 1300 mobile phones and solar chargers were given to households across eight villages in Hpa-An. A call centre based in Yangon then administers short surveys by phone once a month, with households receiving a small financial reward – in the form of airtime credit – for every survey they complete. If households are busy, they’re simply asked for a preferred time to be called back.
This means that not only can we can collect data at roughly a third of the cost of traditional surveys, but it can also be collected when people are on the move. This is necessary in a place like Myanmar where people are increasingly mobile – often seeking temporary work in cities and abroad. Crucially, it means that we have an easier (and less intrusive) way of contacting people after disasters, when gaining access to communities can be slow and high risk. This could be especially useful in instances where people have relocated after a disaster, which would not be possible through normal survey methods.
So far, these methods have allowed the RRR survey to retain 96 percent of the original survey respondents after four separate rounds of surveying. That’s a number that has far exceeded expectations!
The second innovation trials new ways of judging subjective measures of resilience. Resilience has traditionally been measured via objective means – where resilience ‘experts’ come together and decide on a list of indicators that they think make people resilient. This typically includes things that we can see and observe such as household income, education, access to social safety nets, etc.
While methods like these are no doubt useful, they struggle to capture many of the intangible aspects of resilience, such as social networks. Subjective tools, like the ones the RRR effort is trialling, take a very different approach. They start from the position that people have valuable knowledge about what they think makes them resilient.
What have we found so far? Subjective views of resilience are strongly associated with education, poverty, number of household occupants and so on. While traditional assessments reflect many of these, a number of interesting differences exist with objective assessments of resilience.
For example, female-headed households in Hpa-An think of themselves as better able to deal with disasters compared to households headed by men. This flies in the face of many objective surveys that tend to find male-headed households more resilient.
Could it be that female-headed households are able to leverage better social support networks, or tend to have more diverse sources of livelihood pursuits? Could it instead be that there is a psychological difference in how women and men rate themselves? These are questions that the RRR will delve into in the months ahead.
The RRR effort continues to collect large swathes of data. To make this information accessible to all we’ve launched the Resilience Dashboard. This site allows anyone to look in real time at the relationships and trends for themselves.
We hope to learn from those making use of the site to see what potential this new technology and method has, as well as what new ideas it can spark. Above all, we want RRR to generate enthusiasm about innovating and experimenting with different ways of collecting resilience information to help further our understanding of the drivers of resilience.
Only then will we be able to answer the important question: How do we best prioritise limited resources for supporting resilience?
Why we need to rethink ‘maladaptation’
“Maladaptation” is a hot topic in the climate change community. With increasing global attention and finance being poured into adaptation, people are understandably concerned that actions taken to respond to climate change may end up increasing people’s vulnerability now or in the future.
But what does maladaptation actually look like? One example comes from Ho Chi Minh City, Vietnam, where city planners drew up and started to implement many infrastructure projects to help mitigate the risk of flooding. The design of these infrastructural investments was based on the best information and predictions of future climate and development trends available at the time.
However, more recent research suggests that climate change and urbanization will be larger than the Vietnamese anticipated, and in some cases, go beyond the maximum thresholds considered during the projects’ design phase. As a result, city planners are concerned that the very same infrastructure designed to protect people from flooding could in fact lower resilience and make them far more vulnerable in the future.
Lots of processes can cause maladaptation: poor use of climate information in the design of critical long-term
infrastructure, promoting projects that lock people into unsustainable livelihood practices, or failing to factor in the implications of wider development challenges into adaptation projects — such as cultural marginalization of vulnerable groups.
Yet, while we all agree that maladaptation is bad, there is little consensus on what constitutes maladaptation. As a result, we have few — if any — suitable decision support tools to identify and screen for maladaptation. To address this, a new report published by the Pathways to Resilience in Semi-arid Economies research project explores some of the methodological challenges in classifying maladaptation.
So let’s look at four difficult questions and qualities that we need to consider before we are able to assess whether an adaption strategy is maladaptive.
Why is identifying maladaptation so tricky?
First, it’s almost impossible to say whether an adaptation strategy has been “successful” or not: Success can mean different things to different people and without a clear idea of what is and — more importantly — isn’t successful, it is difficult to say an adaptation strategy has been a “success.” Therefore any assessment of maladaptation is inevitably going to be subjective.
Second, at what point do we evaluate maladaptation? What may appear to be successful at a certain point in time may eventually turn out to be harmful to climate risk in the future.
Third, we have to take into account how effective alternative options would have been — something few have considered when it comes to maladaptation. What if you live in an area where all viable adaptation strategies are likely to make people worse off to future climate risk? Perhaps all available strategies will have a heavy cost on society? Our current way of thinking about maladaptation suggests that each of these strategies is likely to be maladaptive. But that doesn’t seem right. Surely an adaptation strategy should be considered partially — or even entirely — successful if it is the best available and reasonable strategy compared with all other options, even if this results in a slight increase in risk?
Fourth, climate risks are changing and evolve over time. This means the baseline we measure progress against is constantly shifting. Yet another reason for confusion and head-scratching!
As these problems showcase, we have a lot of methodological challenges to contend with. But that doesn’t mean that decision-makers should ignore maladaptation. Far from it: If we don’t help decision-makers recognize the risks in promoting maladaptation, and provide them with simple tools to support policymaking, the risk is millions of people’s livelihoods — and lives — will suffer in the long term.
A framework for characterizing maladaptation: 4 cornerstones
So how do we frame maladaptation in a way that recognizes these challenges but is simple enough to use in practice?
In an attempt to offer some solutions, our research proposes a way of framing maladaptation that brings us back to the basics by identifying four building blocks of maladaptation.
The first two relate to what we might consider to be overarching characteristics of maladaptation or the bits that we’re worried about adaptation having a negative impact on:
Climate risk: At its simplest, we should consider an adaptation strategy to be maladaptive if it contributes negatively to the ability of people and communities to deal with and respond to climate change. No surprises here, as this is perhaps the component most commonly associated with maladaptation.
Risk of diminished well-being: In our report we extend the traditional domain of maladaptation considerably by arguing that it’s not sufficient to look simply at climate risk, as adaptation strategies can also have a significant negative impact on people’s livelihoods, culture and economic and social well-being. Therefore, a strategy should also be considered maladaptive if there are large negative effects — unintended or otherwise — on people’s well-being.
We also identify two further building blocks that can be thought of as lenses for looking at how adaptation might affect the two characteristics above:
Distribution: Adaptation strategies can, if poorly implemented, strengthen some people’s ability to deal with climate risk while making it worse for others to adapt; indeed, winners and losers are somewhat inevitable. We therefore need to be careful to look at the impact that any adaptation strategy has on both collective levels of climate risk and well-being. For example, have levels of both increased or been impacted overall? And what about their distribution — has inequality risen as a result?
So, if an adaptation strategy has a large negative impact on the distribution of risk across a system, or if the distribution of impacts on economic and social well-being is significantly uneven, this strategy should be considered maladaptive.
Time: Time is a factor that cuts across all aspects that we’ve mentioned so far, whether that’s risk, well-being or distribution. Put simply, maladaptation occurs when short-term costs or gains outweigh longer-term costs or gains during the period of time of interest. But knowing when to decide on the final outcome is difficult: Maladaptation can occur long after a project has finished. It would be more useful to identify processes that could lead to maladaptation, rather than evaluating maladaptive outcomes at some arbitrarily distant point in time.
While the framework hasn’t got all the answers, it helps us to better classify what should and shouldn’t be called maladaptation. Perhaps what is most important is that we concentrate on identifying what the “symptoms” of maladaptation are or the types of activities that are likely to lead to maladaptive outcomes. These could be poor enabling environments for adaptation, a failure to set up adequate institutions and address power issues, or simply bad planning and management of adaptation strategies. Doing so will help decision-makers and impact evaluators to flag dangerous strategies as early as possible.
Maladaptation isn’t the only thing we should be interested in
Lastly, our research points out that while maladaptation receives considerable policy attention, very little concern goes into addressing the risk that wider development decisions also affect the four building blocks of maladaptation. Yet, most development activities fail to consider climate change in their activities. This means they can’t be considered as adaptation strategies — nor, by that logic, can they be considered maladaptation. Given the considerable impact that social protection schemes, agricultural reform policies or women’s empowerment programs can have on people’s ability to deal with climate change, this is short-sighted.
But it doesn’t really matter what you call it — “maladaptation,” “maladaptation-like” or even “mal-development.” What’s most important is that we get better at ensuring that our current actions don’t increase the risks that climate change poses and don’t negatively impact on our well-being now — or in the future.
However we’re not even close to achieving that goal at the moment. Doing so requires us to move away from abstract discussions of maladaptation, and to plunge straight into the details of how to identify it, screen against it, and prevent it from happening in the first place — however much of a conceptual minefield that might seem.
Lindsey Jones 